Category Archives: American Community Survey

Developing Geographic Relationship Data

.. tools and methods to build and use geographic relationship files … which census blocks or block groups intersect with one or a set of school attendance zones (SAZ)? How to determine which counties are touched by a metropolitan area? Which are contained within a metropolitan area? Which pipelines having selected attributes pass through water in a designated geographic extent? This section reviews use of the Shp2Shp tool and methods to develop a geographic relationship file by relating any two separate otherwise unrelated shapefiles. See relasted Web page for a more detiled review of using Shp2Shp.

As an example, use Shp2Shp to view/determine block groups intersecting with custom defined study/market/service area(s) … the only practical method of obtaining these codes for demographic-economic analysis.

– the custom defined polygon was created using the CV XE GIS AddShapes tool.

Many geodemographic analyses require knowing how geometries geospatially relate to other geometries. Examples include congressional/legislative redistricting, sales/service territory management and school district attendance zones.

The CV XE GIS Shape-to-Shape (Shp2Shp) relational analysis feature provides many geospatial processing operations useful to meet these needs. Shp2Shp determines geographic/spatial relationships of shapes in two shapefiles and provides information to the user about these relationships. Shp2Shp uses the DE-9IM topological model and provides an extended array of geographic and subject matter for the spatially related geometries. Sh2Shp helps users extend visual analysis of geographically based subject matter. Examples:
• county(s) that touch (are adjacent to) a specified county.
• block groups(s) that touch (are adjacent to) a specified block group.
• census blocks correspond to a specified school attendance zone.
• attributes of block groups crossed by a delivery route.

Block Groups that Touch a Selected Block Group
The following graphic illustrates the results of using the Shp2Shp tool to determine which block groups touch block group 48-85-030530-2 — a block group located within McKinney, TX. Shp2Shp determines which block groups touch this block group, then selects/depicts (crosshatch pattern) these block groups in the corresponding GIS map view.

Geographic Reference File
In the process, Shp2Shp creates a geographic relationship file as illustrated below. There are six block groups touching the specified block group. As shown in the above view, one of these block groups touches only at one point. The table below (derived from the XLS file output by Shp2Shp) shows six rows corresponding to the six touching block groups. The table contains two columns; column one corresponds to the field GEOID from Layer 1 (the output field as specified in edit box 1.2 in above graphic) and column 2 corresponds to the field GEOID from Layer 2 (the output field as specified in edit box 2.2 in above graphic). The Layer 1 column has a constant value because a query was set (geoid=’480850305302′) as shown in edit box 1.3. in the above graphic. Any field in the layer dataset could have been chosen. The GEOID may be used more often for subsequent steps using the GRF and further described below. It is coincidental that both layers/shapefiles have the field named “GEOID”.

Layer 1 Layer 2
480850305302 480850305272
480850305302 480850305281
480850305302 480850305301
480850305302 480850305311
480850305302 480850305271
480850305302 480850305312

Note that in the above example, only the geocodes are output for each geography/shape meeting the type of geospatial relationship. Any filed within either shapefile may be selected for output (e.g., name, demographic-economic field value, etc.)

How it Works — Shp2Shp Operations
The following graphic shows the settings used to develop the map view shown above.

See related section providing details on using the Shp2Shp tool.

Geographic Relationships Supported
The Select Relationships dropdown shown in the above graphic is used to determine what type of spatial relationship is to be used. Options include:
• Equality
• Disjoint
• Intersect
• Touch
• Overlap
• Cross
• Within
• Contains
See more about the DE-9IM topological model used by Shp2Shp.

Try it Yourself

See full details on how you can use any version, including the no fee versin, of CV XE GIS to use the Shp2Shp tools. Here are two examples what you can d. Use any of the geospatial relatoinships. Apply your own queries.

Using Touch Operation
Select the type of geographic operation as Touch. Click Find Matches button. The map view now shows as:

Using Contains Operation
Click RevertAll button. Select the type of geographic operation as Contains. Click Find Matches button. The map view now shows as:

Relating Census Block and School Attendance Zones
The graphic shown below illustrates census blocks intersecting with Joyner Elementary School attendance zone located in Guilford County Schools, NC (see district profile). The attendance zone is shown with bold blue boundary. Joyner ES SAZ intersecting blocks are shown with black boundaries and labeled with Census 2010 total population (item P0010001 as described in table below graphic). Joyner ES is shown with red marker in lower right.


– view developed using CV XE GIS and related GIS project; click graphic for larger view

See more about this application in this related Web section.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Accessing & Using ZIP Code Demographics

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

… February 2017 updates .. 5 ways to access/analyze the most recent estimates of median housing value and other subject matter by ZIP Code area .. updates on accessing/downloading/using American Community Survey (ACS1115) 5-year estimates. See more detail in related Web section.

Site analysis (Option 5 below)
– create site analysis profiles from a location/ZIP code.

Contents
Five data access and use options, listed in the links below, are reviewed. Each method illustrates how ZIP code demographic-economic data can be accessed/ analyzed/used in different contexts. The most basic data access/data download is illustrated in Option 3. The following links open new windows that take you to the related section with more detail.
Option 1 – View the data as a thematic pattern map.
Option 2 – View, compare, rank query data in interactive tables.
Option 3 – Access data using API Tools; create datasets.
.. Option 3a – Extended ZIP Code subject matter access.
.. Option 3b – ZIP code urban/rural data access.
.. Option 3c – Additional API ACS data access resources.
Option 4 – View $MHI in structured profile in context of related data.
Option 5 – Site analysis – view circular area profile from a location.

Related ZIP Code Data Access & Use sections
Interactive access to demographics based on an address
Summary of ZIP Code Data Resources & Tools
10 Reasons to use Census Tracts Versus ZIP Codes
Analyzing Census Tract Demographics by ZIP Code Area
ZIP Code to Census Tract Equivalence Table
ZIP Code Urban/Rural Geography & Demographics
Mapping ZIP Code Demograhics
Housing Price Index by 5-digit ZIP Code – time series; annual updates
Housing Price Index by 3-digit ZIP Code – time series; quarterly updates
ZIP Code Business Establishment, Employment & Earnings by industry
ZIP Code Retail Trade Establishment & Sales by industry
ZIP Code Equivalence Tables — ZIP Code to School District

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

National Children & Education Statistics Program Updates

.. NCES Program updates .. tools, data & methodology to examine national scope children & education .. school, school district & extended geographic-statistical data with drill-down to school and intersection level. See more about the NCES Program below.

New this Week
ACS 2015 school district demographic-economic interactive tables
– view, compare, analyze selected/all U.S. school districts
– more focused blog updates coming soon.

School Districts with Highest Median Household Income
Use the interactive table to examine economic characteristics of school districts. Below is a list of the 10 school districts having the highest median household income developed using the Economic Characteristics interactive table. Develop similar views for metros and states of interest.

– ranked on item E062 — median household income.
– click graphic for larger view.

Use GIS tools to develop thematic pattern maps such as the one shown below with NCES GIS projects. Select from hundreds of statistical measures. Create your own regional;/district views. Integrate other data.

Patterns of Economic Prosperity by School District
– median household income (item E062 in table)

– view developed with CVGIS software & related GIS project and data.
– click graphic for larger view.

See the School Districts Economic Characteristics Interactive Table.

About the National Children & Education Statistics Program
The National Children & Education Statistics (NCES) Program provides access to tools, data & methodology to examine national scope children’s demographics & education-related characteristics. These resources enable stakeholders to view and analyze detailed geographic and statistical data at the school, neighborhood, community, attendance zone, school district and higher level geography. Integrate these data with drill-down demographic-economic data to the census block and intersection levels. Examine characteristics of schools, school districts and education data with related and higher level geography including urban/rural, cities, counties, metros, state and the U.S.

See NCES Main Section.

Contents: Summary of NCES Program Resources
Click a link to view more detail on a selected topic.
Updates: New Resources, Events & Related Topics
Analytics, Blogs, Studies
Using Software Tools & Datasets
01 Mapping & Visual Analysis Tools
02 School District Annual Demographic-Economic Data Resources
03 Children’s Demographics & Living Environment by School District
04 School District Enrollment & Operational Characteristics
05 School District Finances: Sources & Uses of Funds
06 School District Geographic Size & Characteristics
07 School District-ZIP Code Area Relationship Table
08 K-12 Public Schools
09 K-12 Private Schools
10 K-12 Public School Attendance Zones
11 K-12 Public Schools by Urban/Rural Status
12 Census Tract Demographic-Economic Characteristics
13 Metropolitan Area Situation & Outlook Reports

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

ZIP Codes with Highest & Lowest Economic Prosperity

.. the latest data for ZIP Code Areas show that eleven had a median household income of $250,000 or more during the period 2011-15. More than 20 ZIP code areas had a median housing value of $2,000,000 or more. Contrast these ZIP code areas with higher economic prosperity with the more than 150 ZIP codes that had a median housing value of less than $30,000.  Use the interactive table in this related Web section to see which ZIPs meet these and other criteria.

ZIP Codes with MHI $100,000 or More; Dallas, TX Metro
Analyzing economic prosperity patterns using combined types of small area geography … the following graphic shows ZIP code areas a red markers with the median household income or $100,000 or more in context of median household income by census tract thematic pattern. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view for your areas of interest. .

– view developed with CV XE GIS software.

This section reviews measures of economic prosperity for all ZIP code areas. These data were released in December 2016. This section updates with new data December 2017. See the list of all ZIP ccdes showing population, housing and economic characteristics in the interactive table shown below. Use the interactive table to view, rank, compare and query ZIP code attributes.

Examining demographic-economic characteristics by ZIP code is important for several reasons. We are familiar with our own ZIP codes as a geographic location. We tend to be interested in our area compared to other areas. ZIP codes provide an easy way to do that. Also, many secondary data resources are tabulated by ZIP code area; some important data are only available by ZIP code. See more about ZIP Code areas.

Resources & Methods to Examine Small Area Demographics
• See related ZIP Code Demographic-Economic Interactive Tables
  .. extended subject matter
• See related Census Tract Code Demographic-Economic Interactive Tables
• Examine ZIP Code Urban/Rural Characteristics
• Examine ZIP Code Business Establishment patterns
• Examine ZIP Code Housing Price Index patterns
• Join us in the weekly Data Analytics Lab Sessions
  .. reviewing applications using these and related data.

ZIP Code Areas with $MHI $100,000 or More
The following graphic shows ZIP code areas as red markers having median household income or $100,000 or more. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas with $MHV Less than $30,000
The following graphic shows ZIP code areas as orange markers having median housing value of less than $30,000. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas: Population & Economic Prosperity
  — Interactive Table –
Use the interactive table to view, rank, compare, query ZIP codes based on a selection of demographic-economic measures. The following graphic illustrates how the table can be used to examine patterns of the three digit ZIP code area (San Diego) by 5-digit ZIP code. Table operations are used to select ZIP codes in the 921 3-digit area (containing 39 5-digit ZIP codes). These 39 ZIP code are then ranked in descending order on median household income. See results in the table shown below. ZIP code 92145 has the highest $MHI in this group with $228.036.

– click graphic for larger view.

Try it yourself. Use the table to examine a set of ZIP codes on your selected criteria in for a state/area of interest.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Examining Health Characteristics by Census Tract

.. new data, new ways to examine health characteristics at the city and census tract/subcounty level.  For example, among the 500 largest U.S. cities in 2014, the incidence of high blood pressure ranged from 22.5% (Longmont, CO) to 47.8% (Gary, IN). Use the interactive table to view, rank, compare this and other new wide-ranging health statistics for the 500 largest U.S. cities and associated census tracts. See the related Web section for more detail.

At the census tract/neighborhood level, 937 tracts have more than 10% of the population ages 18 years and over with coronary heart disease. What are characteristics of health-related factors in your city, neighborhood and census tracts of interest? Use tools reviewed in this section to access/analyze a wide range of health-related characteristics (see items list below) — not available at the city or census tract level before.

Patterns of High Blood Pressure: Honolulu, HI by Census Tract
This graphic illustrates visual analysis and analytical potential for tracts in cities covered.

– Click graphic for larger view with high blood pressure %population label
– View developed with CV XE GIS software and related GIS project/fileset.

Accsss/analyze these data for approximately 28,000 tracts (of a total approximate 74,000) on topics including chronic disease risk factors, health outcomes and clinical preventive service use for the largest 500 cities in the U.S. These small area data enable stakeholders in cities, local health departments, neighborhoods and study areas to better understand the characteristics and geographic distribution of health-related measures and how they might impact health-related programs and other demographic-economic issues.

Scope of 500 Cities
The following graphic shows the 500 cities (green areas) included in project. Data for these cities and intersecting tracts are available. Click graphic for larger view providing county visibility and city name labels. Expand browser to full window for best quality view.

– View developed with CV XE GIS software and related GIS project/fileset.

The 500 Cities data have been developed as a part of the CDC 500 Cities project, a collaboration between the Centers for Disease Control (CDC), the Robert Wood Johnson Foundation and the CDC Foundation. These data are being integrated into the Situation & Outlook (S&O) database and included in the S&O metro reports. Examine health-related characteristics of metro cities and drill-down areas in combination with other demographic-economic measures.

Analytical Potential
These data provide only the health characteristics attributes. They are a small, but important, subset of a larger set of key health metrics. These data are estimates subject to errors of estimation and provide a snapshot view of one point in time.

The value of these data can be leveraged by linking them with other demographic-economic data from the American Community Survey (ACS 2015) tract and city data. Integrate and analyze these data with related data and alternative geography. See related health data analytics section.

Patterns of Heart Disease; Charlotte, NC-SC Area by Tract
This graphic illustrates coronary heart disease patterns by census tract for cities included in the database. Gray areas are census tracts not included in the 500 cities database. Click graphic for larger view.
– View developed with CV XE GIS software and related GIS project/fileset.

Using the Interactive Table
Use the interactive table to view, rank, compare, query these health measures by city. The following graphic illustrates how the table can be used to examine patterns of Texas cities. Table operations are used to selected Texas cities then rank the cities based on the “Access” column — “Current lack of health insurance among adults aged 18-64 Years”.

Try it yourself. Use the table to examine a set of cities in a state of interest.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

2016 Presidential Election – Voting & Citizen Voting Age Population by County

In 2015, the U.S. citizen voting age population (CVAP) was 227,019,486 of the total U.S. resident population of 321,418,821 (70.6%). 2016 CVAP data are not yet available. In the 2016 presidential election, 128,298,470 votes were cast — approximately 56% of the citizen voting age population. For individual counties the 2016 presidential election vote ranged from 16% of the CVAP to near 100%. Use the interactive table in this section to examine characteristics of the 2016 presidential election vote and citizen voting age population by county.

This section reviews access to tools to view/analyze characteristics of the U.S. voting population (ages 18 and older and citizen) and participation in the 2016 presidential election. Data are based on Census Bureau annual population estimates, American Community Survey 2010-14 5 year (ACS 2014) Citizen Voting Age Population (CVAP) special tabulation and 2016 presidential election results.

Visual Analysis of 2016 Presidential Election Vote by County
The following graphic shows the 2016 presidential vote as a percent of the citizen voting age population.

– Click graphic for larger view.
– View developed with CV XE GIS software.

U.S. Electorate Profile: Characteristics of the Citizen, 18 and Older Population

– based on 2015 American Community Survey 1-Year estimates
*Except where noted, “race” refers to people reporting only one race.
**Hispanic refers to the ethnicity category and may be of any race.
***Households with citizen householders.

U.S. by County Interactive Table Analysis 
Use the interactive table to examine characteristics of the 2016 presidential election vote and citizen voting age population by county. The following graphic illustrates how the table can be used to examine patterns in the Houston, TX metro by county. The Find in CBSA button is used below the table to select only counties in this CBSA/metro. The rightmost column header cell is clicked to rank counties on the voter participation rate for the 2016 presidential election.

– click graphic for larger view.

Try it yourself. Use the table to examine a set of counties in a metro or state of interest.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Mapping Census Tract Demographics

.. using visual data analytics and developing business intelligence .. this section provides a 4-step procedure to develop thematic pattern and reference maps for census tracts. The focus of this section is on mapping Census 2010 census tracts using data from the 2014 American Community Survey (ACS2014). A similar set of steps could be followed for Census 2000 tracts with Census 2000 data or Census 2010 tracts with Census 2010 demographics or different vintage ACS data. Steps summarized here can be used with most any Windows-based computer having Internet access. See the related full Web section with more details.

• how do customers and sales relate to market area characteristics?
• is their a better configuration of locations or service areas?
• how can you more effectively examine customer and sales patterns?
• what and where are areas of missed opportunities?

See related sections:
Using GIS & Data Analytics
Mapping Statistical Data

Benefits of this section include providing help for those:
• having a specific interest in mapping census tract demographics.
• with little or no experience in using GIS.
• getting started with CVGIS.

These resources and instructions provide a real, not demo, valuable tool that anyone can use, without fee, to create county by census tract thematic pattern maps. Use any of the “richer” demographic-economic data (not just median household income) from the latest ACS 5-year data (see scope — table shells xls).

The steps described below can be performed with any version of CVGIS, including the no fee version. Start from scratch and develop thematic pattern maps like that shown below. Questions, need help? See the FAQs. Call with questions – 888.364.7656. Or, use this form and put questions in the text section.

While this application is focused on ACS 2014 median household income for Dallas County, TX census tracts, you can follow these steps for other areas and subject matter. In your own applications, choose any ACS subject matter for any county/area of interest. The following view shows the end result of steps described below. Choose your own county of state; choose your own subject matter; select your own colors and labeling; choose your own zoom view; and more. Dallas Metro Situation & Outlook.

Patterns of Economic Prosperity; Dallas County, TX by Tract

Mapping Census Tracts Demographics Steps
These steps should take an inexperienced user 10-15 minutes to develop a new CVGIS project view. Steps can be performed at separate times.
Click on a link to view step-by-step instructions.
1. Install CVGIS
2. Get census tract shapefile
3. Get census tract subject matter data (median household income or other)
4. Create map view(s)

Create your own maps for your own county/tracts for your own subject matter.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.